Events

  • 2019
  • Past events
  • Seminar: The dynamics of social conventions: From names to cryptocurrencies

    Speaker
    Andrea Baronchelli (City University of London)

    Description

    How do conventions emerge and evolve in complex decentralized social systems? This question engages fields as diverse as sociology, economics, cognitive science and network science. Various attempts to solve this puzzle pre-suppose that formal or informal institutions are needed to facilitate a solution. The complex systems approach, by contrast, hypotheses that such institutions are not necessary. In this talk, I will discuss theoretical and experimental results that demonstrate the spontaneous creation of universally adopted social conventions. Then, I will discuss how social norms change, showing how historical data and lab experiments indicate that abrupt transitions between competing norms do not require the intervention of a centralized authority. Finally, I will present some recent results on the modelling of the cryptocurrency market, where users conventionally attribute value to electronic tokens. Overall, these results clarify the processes of social coordination and can help identify and/or design collective behavioural change online or offline.

  • 2019 UBICS Day

    Description

    The Universitat de Barcelona Institute of Complex Systems (UBICS) celebrates its annual meeting.

  • Seminar: Winning the Big Data Technologies Horizon Prize: Fast and reliable forecasting of electricity grid traffic by identification of recurrent fluctuations

    Speaker
    Jose M.G. Vilar (Biofisika Institute (CSIC-UPV/EHU) University of the Basque Country)

    Description

    I will comment on the approach and methodology I used in winning the European Union Big Data Technologies Horizon Prize on data-driven prediction of electricity grid traffic. The methodology relies on identifying typical short-term recurrent fluctuations, which is subsequently refined through a regression-of-fluctuations approach. I will also emphasize the key points and strategic considerations that led to selecting or discarding different methodological aspects. The criteria include adaptability to changing conditions, reliability with outliers and missing data, robustness to noise, and efficiency in implementation.

  • VIII Jornada Complexitat.cat

  • Seminar: Using graphs and statistical physics to build a Bayesian machine scientist

    Speaker
    Roger Guimerà, ICREA & Universitat Rovira i Virgili

    Description

    Since the scientific revolution, interpretable closed-form mathematical models have been instrumental for advancing our understanding of the world. Think, for example, of Newton’s law of gravitation, and how it has enabled us to predict astronomical phenomena with great accuracy and to gain deep insights about seemingly unrelated physical phenomena. With the data revolution, we may now be in a position to uncover new mathematical models for many systems, from physics and chemistry to the social sciences. However, to deal with increasing amounts of data, we need approaches that are able to extract these models automatically, without supervision, and with guarantees of asymptotically finding the correct model. In this talk I will review standard machine learning approaches and discuss their limitations in terms of getting interpretable models. Then, I will present a Bayesian "machine scientist" that deals rigorously with model plausibilities and also explores systematically the space of models, using the analogy between Bayesian inference, information theory, and statistical mechanics. The machine scientist is able to obtain closed-form mathematical models from data, and to make out-of-sample predictions that are more accurate than those of standard machine learning approaches.